Public record
Software health reportschema 0.26.0 · metrics 2.10.0 · 2026-07-22 07:57 UTC

Xilinx / brevitas

Brevitas: neural network quantization in PyTorch

PythonCustom license★ 1,554 stars⑂ 246 forkssince Jul 2018View on GitHub ↗

Xilinx/brevitas holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (95/100) and lowest on Security (21/100). It was last updated today. 2 contributors account for most of its recent work.

89
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

89
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 75 is calibrated to 89 on the published index scale (record calibration 2026-08-02).

Ownership

XilinxOrganization
3,063 followers465 public repossince Jan 2013

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIbrevitas0.13.0-207 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

93Exceptional · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
30.5/36Commit cadence44/52 weeks with commits
18/18Commit volume143 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year143
human_commit_share1
days_since_last_push0
active_weeks_last_year44
How it's scored
27/27Ships releases38 releases published
36/36Release recencylatest release 7 days ago
19.8/27Release cadencea release every ~105.4 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count38
latest_release_tagv0.13.0
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases105.4

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

76Good · 17% of overall
How it's scored
51.8/60Stars1,554 stars
19.9/25Forks246 forks
8.1/15Watchers30 watchers
Inputs used
forks246
stars1,554
watchers30
growth_stateorganic
growth_factor_pct100
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

81Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
11.9/22.5Commit distributiontop contributor authored 47% of commits
13.5/13.5Contributor breadth26 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor2
contributors_sampled26
top_contributor_share0.471
How it's scored
28/42Issue resolution67% of issues closed
26/30PR acceptance803/927 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs803
open_issues178
closed_issues357
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.667
closed_unmerged_prs124
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
25/25Owner reach3,063 followers of Xilinx
25/25Track record465 public repos, account ~13 yr old
Inputs used
followers3,063
owner_typeOrganization
is_verified
owner_loginXilinx
public_repos465
account_age_days4,946
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 7 days ago
20/20Version history20 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesbrevitas
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall
How it's scored
24/24CI workflows27 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://xilinx.github.io/brevitas/
10/10Repository description
10/10Topics10 topics
10/10Wiki
Inputs used
topicsquantization, pytorch, brevitas, fpga, neural-networks, hardware-acceleration, xilinx, deep-learning, ptq, qat
has_wikiyes
homepagehttps://xilinx.github.io/brevitas/
docs_sitehttps://xilinx.github.io/brevitas/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

21At Risk · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsrequirements/requirements-dev.txt, requirements/requirements-diffusion.txt, requirements/requirements-docs.txt, requirements/requirements-export.txt, requirements/requirements-finn-integration.txt, requirements/requirements-hadamard.txt, requirements/requirements-lighteval.txt, requirements/requirements-llm.txt, requirements/requirements-notebook.txt, requirements/requirements-nox.txt, requirements/requirements-numpy.txt, requirements/requirements-ort-integration.txt, requirements/requirements-setup.txt, requirements/requirements-stt.txt, requirements/requirements-test.txt, requirements/requirements-tts.txt, requirements/requirements-vision.txt, requirements/requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories49
affected_packages3
assessed_packages23
unassessed_packages48
affected_by_severitycritical 1, high 2
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 23 resolved dependencies against OSV. 48 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

57Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history82 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.82
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdocsrc/Makefile, noxfile.py
22/22Automated tests
11/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocsrc/Makefile, noxfile.py
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
50.3/55Manageable file sizes54/627 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes315,737
source_files_sampled627
oversized_source_files54
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesnotebooks
Inputs used
example_dirsnotebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

1,554GitHub stars
26contributors
143commits, last 12 months
0days since last push
38releases
2bus factor
178open issues
PyPIpackage ecosystems

Data collection warnings

  • deps.dev does not index pypi:brevitas@0.13.0; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard did not return a usable result (exit code -9); skipping Scorecard checks

More detail

Star and fork history 1,554 ★ / 246 ⇿
1,554Stars
246Forks
38Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

04008001,2001,6001,554242172018-112022-092026-07
Major 0Minor 12Patch 9

Each point covers 8 days.

All dependencies 71

Full resolved dependency set from the GitHub dependency graph: 0 direct and 71 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaccelerateindirect
PyPIaccelerate1.0.1indirect
PyPIbitstringindirect
PyPIdatasetsindirect
PyPIdependencies2.0.1indirect
PyPIdiffusersindirect
PyPIdiffusers0.30.3indirect
PyPIgguf0.18.0indirect
PyPIhypothesisindirect
PyPIinflect5.6.2indirect
PyPIjupyterindirect
PyPIlibrosaindirect
PyPIlighteval0.13indirect
PyPIlxml4.9.3indirect
PyPIm2r20.3.3.post2indirect
PyPImockindirect
PyPInbmakeindirect
PyPInbsphinx0.9.3indirect
PyPInbsphinx-link1.3.0indirect
PyPInoxindirect
PyPInumbaindirect
PyPInumexprindirect
PyPInumpyindirect
PyPIonnxindirect
PyPIonnxoptimizerindirect
PyPIonnxruntimeindirect
PyPIonnxscriptindirect
PyPIopen-clip-torch2.26.1indirect
PyPIopencv-python4.10.0.84indirect
PyPIoptimumindirect
PyPIpackagingindirect
PyPIpandasindirect
PyPIpandas2.2.2indirect
PyPIpillowindirect
PyPIpre-commitindirect
PyPIpsutilindirect
PyPIpycocotools2.0.7indirect
PyPIpydanticindirect
PyPIpydata-sphinx-theme0.15.3indirect
PyPIpytestindirect
PyPIpytest-casesindirect
PyPIpytest-mockindirect
PyPIpytest-xdistindirect
PyPIpyyamlindirect
PyPIqonnxindirect
PyPIrequestsindirect
PyPIruamel-yamlindirect
PyPIscipyindirect
PyPIscipy1.10.1indirect
PyPIsetuptoolsindirect
PyPIsetuptools-scmindirect
PyPIsoundfileindirect
PyPIsoxindirect
PyPIsphinx5.3.0indirect
PyPIsphinx-autodoc-typehints1.21.8indirect
PyPIsphinx-gallery0.10.1indirect
PyPIsphinxcontrib-napoleon0.7indirect
PyPIsphinxemoji0.2.0indirect
PyPIsympyindirect
PyPItoposortindirect
PyPItorchindirect
PyPItorch-stftindirect
PyPItorchmetricsindirect
PyPItorchmetrics1.4.3indirect
PyPItorchvisionindirect
PyPItqdmindirect
PyPItransformersindirect
PyPItransformers4.45.2indirect
PyPItyping-extensionsindirect
PyPIunfoldndindirect
PyPIunidecodeindirect
Dependency advisories 3

This repository publishes no package the index resolves, so its own dependency graph was assessed — 23 packages, which also include development and test pins that never ship: 3 carry known advisories, of which 0 are direct. 48 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
transformers4.45.2indirectcritical425.5.0
diffusers0.30.3indirecthigh50.38.0
lxml4.9.3indirecthigh26.1.0

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.26.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.